A collective computation approach to automatic target recognition

Author

Baran, Robert H.

Author_Institution

US Naval Surface Warfare Center, Silver Spring, MD, USA

fYear

1989

fDate

0-0 1989

Firstpage

39

Abstract

A neural network associative memory is used to guide the template-matching process in a digital simulation model of a third-generation fuse. The templates are produced by analytic models of target interaction with several simultaneous sensors and are stored by means of the Hinton-Sejnowski formula in a symmetrically cross-coupled (Hopfield) network. A description is given of some salient features of network design and simulation. The performance gain that can be achieved with this collective computation approach is limited mainly by the size of the network.<>

Keywords

computerised pattern recognition; computerised picture processing; content-addressable storage; digital simulation; military computing; neural nets; weapons; Hinton-Sejnowski formula; Hopfield network; automatic target recognition; collective computation approach; computer vision; digital simulation model; military computing; neural network associative memory; symmetrically cross-coupled network; template-matching process; third-generation fuse; Associative memories; Image processing; Military computing; Neural networks; Pattern recognition; Simulation; Weapons;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1989. IJCNN., International Joint Conference on

Conference_Location

Washington, DC, USA

Type

conf

DOI

10.1109/IJCNN.1989.118557

Filename

118557